Apache Flink Worst Practices - Konstantin Knauf

Distributed stream processing is evolving from a technology in the sidelines of Big Data to a key enabler for businesses to provide more scalable, real-time services to their customers. We at Ververica, the company founded by the original creators of Apache Flink, and other prominent players in the Flink community have witnessed this development from the driver’s seat. Working with our customer and the wider community we have seen great success stories and we have seen things going wrong. In this talk, I would like to share anecdotes and hard-learned lessons of adopting distributed stream processing – Apache Flink specific as well as across frameworks. Afterwards, you will know, how not to model your use cases as a stream processing application, which data structures not to use, how not to deal with failure, how not to approach the topic of monitoring and much more.

[Jakt]

It seems to me that such keynote seems necessary as Flink does not have a nice way to promote best practices.
Flink seems a framework that is not that very flexible on its usage since many things are handled under the hood by the framework itself such as State and Checkpointing.
If static variables and Threads do not work well with Flink then the framework should try to prevent you from going into that direction both through its usage and through the documentation which is still quite lacking unfortunately. All the info on this video should be part of a QA in the official documentation IMHO.